1. Technical Field
The present disclosure relates to tagging audio content and more specifically to generating personalized tag recommendations for tagging audio content.
2. Introduction
When listening to an audio conversation or participating in the audio conversation, users often annotate the audio conversation with tags to provide additional information about the audio conversation. The tags can include information about a topic in the audio conversation, the quality of the discussion in the audio conversation, the speakers in the audio conversation, information about a segment in the audio conversation, etc. For example, the tags can identify a subject of discussion in the audio conversation. As another example, the tags can describe the discussion in the audio conversation. This information about the audio conversation provided by the tags can then help the users identify which audio conversations or segments are of interest to them, for example. The tags can also make the audio conversation searchable, so users can search information associated with the audio conversation based on the tags in the audio conversation.
Not surprisingly, the information provided by the tags in an audio conversation increases as more tags are added to the audio conversation. Unfortunately, users often limit the amount of tags they provide during an audio conversation. This is largely because creating different tags throughout an audio conversation can be an onerous task for the user. Moreover, the user can easily get interrupted or distracted when creating tags in an audio conversation. As a result, users are reluctant to create and add tags for an audio conversation. Consequently, the benefit and amount of information provided by the limited tags diminish.
To increase the amount of tags in an audio conversation, some systems try to automatically tag the audio conversation with tags generated by the system. However, these tags typically do not include any user input, and, therefore, are not personalized and are often inaccurate and imprecise. Some systems try to obtain user input by presenting tag recommendations to the user for the user to select the most accurate and useful tags. This allows the user to add tags to an audio conversation by simply accepting tag recommendations. Moreover, the user is more likely to add tags to the audio conversation when the process is simplified in this manner. As a result, the tag recommendations often yield a greater number of tags added to the audio conversation. However, such tag recommendations do not use the audio content and other useful information to determine which tags to recommend. Rather, such tag recommendations are typically based on the user's history, which does not provide a complete and accurate representation of the most relevant and useful information for recommending tags to the user.